Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Genetic variation in selenoprotein S influences inflammatory response


Chronic inflammation has a pathological role in many common diseases and is influenced by both genetic and environmental factors. Here we assess the role of genetic variation in selenoprotein S (SEPS1, also called SELS or SELENOS), a gene involved in stress response in the endoplasmic reticulum and inflammation control. After resequencing SEPS1, we genotyped 13 SNPs in 522 individuals from 92 families. As inflammation biomarkers, we measured plasma levels of IL-6, IL-1β and TNF-α. Bayesian quantitative trait nucleotide analysis identified associations between SEPS1 polymorphisms and all three proinflammatory cytokines. One promoter variant, −105G → A, showed strong evidence for an association with each cytokine (multivariate P = 0.0000002). Functional analysis of this polymorphism showed that the A variant significantly impaired SEPS1 expression after exposure to endoplasmic reticulum stress agents (P = 0.00006). Furthermore, suppression of SEPS1 by short interfering RNA in macrophage cells increased the release of IL-6 and TNF-α. To investigate further the significance of the observed associations, we genotyped −105G → A in 419 Mexican American individuals from 23 families for replication. This analysis confirmed a significant association with both TNF-α (P = 0.0049) and IL-1β (P = 0.0101). These results provide a direct mechanistic link between SEPS1 and the production of inflammatory cytokines and suggest that SEPS1 has a role in mediating inflammation.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1
Figure 2: Pattern of linkage disequilibrium in SEPS1.
Figure 3: Results of robust measured genotype analysis for marginal associations between SEPS1 SNPs and plasma cytokine measures.
Figure 4: Effect of SEPS1 SNP −105G → A on expression of SEPS1 after challenging HepG2 cells with tunicamycin.
Figure 5: siRNA suppression of SEPS1 in macrophages.


  1. Walder, K. et al. Tanis: a link between type 2 diabetes and inflammation? Diabetes 51, 1859–1866 (2002).

    Article  CAS  Google Scholar 

  2. Gao, Y. et al. Elevation in Tanis expression alters glucose metabolism and insulin sensitivity in H4IIE cells. Diabetes 52, 929–934 (2003).

    Article  CAS  Google Scholar 

  3. Kryukov, G.V. et al. Characterization of mammalian selenoproteomes. Science 300, 1439–1443 (2003).

    Article  CAS  Google Scholar 

  4. Ye, Y., Shibata, Y., Yun, C., Ron, D. & Rapoport, T.A. A membrane protein complex mediates retro-translocation from the ER lumen into the cytosol. Nature 429, 841–847 (2004).

    Article  CAS  Google Scholar 

  5. Karlsson, H.K., Tsuchida, H., Lake, S., Koistinen, H.A. & Krook, A. Relationship between serum amyloid A level and Tanis/SelS mRNA expression in skeletal muscle and adipose tissue from healthy and type 2 diabetic subjects. Diabetes 53, 1424–1428 (2004).

    Article  CAS  Google Scholar 

  6. Pahl, H.L. & Baeuerle, P.A. The ER-overload response: activation of NF-kappa B. Trends Biochem. Sci. 22, 63–67 (1997).

    Article  CAS  Google Scholar 

  7. Zamani, M., Pociot, F., Raeymaekers, P., Nerup, J. & Cassiman, J.J. Linkage of type I diabetes to 15q26 (IDDM3) in the Danish population. Hum. Genet. 98, 491–496 (1996).

    Article  CAS  Google Scholar 

  8. Field, L.L., Tobias, R. & Magnus, T. A locus on chromosome 15q26 (IDDM3) produces susceptibility to insulin-dependent diabetes mellitus. Nat. Genet. 8, 189–194 (1994).

    Article  CAS  Google Scholar 

  9. Blacker, D. et al. Results of a high-resolution genome screen of 437 Alzheimer's disease families. Hum. Mol. Genet. 12, 23–32 (2003).

    Article  CAS  Google Scholar 

  10. Susi, M., Holopainen, P., Mustalahti, K., Maki, M. & Partanen, J. Candidate gene region 15q26 and genetic susceptibility to coeliac disease in Finnish families. Scand. J. Gastroenterol. 36, 372–374 (2001).

    Article  CAS  Google Scholar 

  11. Saadeddin, S.M., Habbab, M.A. & Ferns, G.A. Markers of inflammation and coronary artery disease. Med. Sci. Monit. 8, RA5–12 (2002).

    CAS  PubMed  Google Scholar 

  12. Cheverud, J.M. A simple correction for multiple comparisons in interval mapping genome scans. Heredity 87, 52–58 (2001).

    Article  CAS  Google Scholar 

  13. Abecasis, G.R., Cherny, S.S., Cookson, W.O. & Cardon, L.R. Merlin–rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 30, 97–101 (2002).

    Article  CAS  Google Scholar 

  14. Almasy, L. & Blangero, J. Multipoint quantitative-trait linkage analysis in general pedigrees. Am. J. Hum. Genet. 62, 1198–1211 (1998).

    Article  CAS  Google Scholar 

  15. Abecasis, G.R., Cookson, W.O. & Cardon, L.R. Pedigree tests of transmission disequilibrium. Eur. J. Hum. Genet. 8, 545–551 (2000).

    Article  CAS  Google Scholar 

  16. Blangero, J. et al. Quantitative trait nucleotide analysis using Bayesian model selection. Hum. Biol. (in the press).

  17. Gao, Y. et al. Regulation of the selenoprotein SelS by glucose deprivation and endoplasmic reticulum stress - SelS is a novel glucose-regulated protein. FEBS Lett. 563, 185–190 (2004).

    Article  CAS  Google Scholar 

  18. de Maat, M.P. et al. Genetic influence on inflammation variables in the elderly. Arterioscler. Thromb. Vasc. Biol. 24, 2168–2173 (2004).

    Article  CAS  Google Scholar 

  19. Pantsulaia, I., Trofimov, S., Kobyliansky, E. & Livshits, G. Genetic and environmental influences on IL-6 and TNF-alpha plasma levels in apparently healthy general population. Cytokine 19, 138–146 (2002).

    Article  CAS  Google Scholar 

  20. Williams-Blangero, S. et al. Genetic influences on plasma cytokine variation in a parasitized population. Hum. Biol. 76, 515–525 (2004).

    Article  Google Scholar 

  21. Blangero, J., Williams, J.T. & Almasy, L. Novel family-based approaches to genetic risk in thrombosis. J. Thromb. Haemost. 1, 1391–1397 (2003).

    Article  CAS  Google Scholar 

  22. Stengard, J.H. et al. Contributions of 18 additional DNA sequence variations in the gene encoding apolipoprotein E to explaining variation in quantitative measures of lipid metabolism. Am. J. Hum. Genet. 71, 501–517 (2002).

    Article  CAS  Google Scholar 

  23. Altshuler, D. et al. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat. Genet. 26, 76–80 (2000).

    Article  CAS  Google Scholar 

  24. Caspersen, C., Pedersen, P.S. & Treiman, M. The sarco/endoplasmic reticulum calcium-ATPase 2b is an endoplasmic reticulum stress-inducible protein. J. Biol. Chem. 275, 22363–22372 (2000).

    Article  CAS  Google Scholar 

  25. Kokame, K., Kato, H. & Miyata, T. Identification of ERSE-II, a new cis-acting element responsible for the ATF6-dependent mammalian unfolded protein response. J. Biol. Chem. 276, 9199–9205 (2001).

    Article  CAS  Google Scholar 

  26. Roy, B. & Lee, A.S. The mammalian endoplasmic reticulum stress response element consists of an evolutionarily conserved tripartite structure and interacts with a novel stress-inducible complex. Nucleic Acids Res. 27, 1437–1443 (1999).

    Article  CAS  Google Scholar 

  27. Arthur, J.R. Selenium supplementation: does soil supplementation help and why? Proc. Nutr. Soc. 62, 393–397 (2003).

    Article  CAS  Google Scholar 

  28. Ferencik, M. & Ebringer, L. Modulatory effects of selenium and zinc on the immune system. Folia Microbiol. (Praha) 48, 417–426 (2003).

    Article  CAS  Google Scholar 

  29. Kissebah, A.H. et al. Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome. Proc. Natl. Acad. Sci. USA 97, 14478–14483 (2000).

    Article  CAS  Google Scholar 

  30. MacCluer, J.W. et al. Genetics of atherosclerosis risk factors in Mexican Americans. Nutr. Rev. 57, S59–S65 (1999).

    Article  CAS  Google Scholar 

  31. Buetow, K.H. et al. High-throughput development and characterization of a genomewide collection of gene-based single nucleotide polymorphism markers by chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Proc. Natl. Acad. Sci. USA 98, 581–584 (2001).

    Article  CAS  Google Scholar 

  32. Phillips, P.C. From complex traits to complex alleles. Trends Genet. 15, 6–8 (1999).

    Article  CAS  Google Scholar 

  33. Long, A.D., Lyman, R.F., Langley, C.H. & Mackay, T.F. Two sites in the Delta gene region contribute to naturally occurring variation in bristle number in Drosophila melanogaster. Genetics 149, 999–1017 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Kass, R.E. & Raftery, A.E. Bayes factors. J. Am. Stat. Assoc. 90, 773–795 (1995).

    Article  Google Scholar 

  35. Raftery, A.E. Bayesian model selection in social research. in Sociological Methodology (ed. Marsden, P.V.) 111–195 (Blackwells, Oxford, 1995).

    Google Scholar 

Download references


This work was supported by grants from the National Institutes of Health. Take Off Pounds Sensibly, Inc. provided funds for establishment of the family database and clinical phenotyping. This work was also supported by grants from the National Center for Research Resources to the General Clinical Research Centers at the Medical College of Wisconsin and the University of Texas Health Science Center San Antonio. The statistical genetics computer package, SOLAR, is supported by a grant from the National Institutes of Mental Health. The supercomputing facilities used for this work at the SBC Genetics Computing Center were supported in part by a gift from the SBC Foundation. Funds for resequencing, genotyping and functional and statistical analyses were provided by ChemGenex Pharmaceuticals Ltd., Australia.

Author information

Authors and Affiliations


Corresponding author

Correspondence to John Blangero.

Ethics declarations

Competing interests

Funds for resequencing, genotyping and functional and statistical analyses were provided by ChemGenex Pharmaceuticals, which has a patent on SELS in relation to its role in multiple diseases. G.R.C. and P.Z. have personal financial interests in ChemGenex. G.R.C. is also the Chief Executive Officer and Managing Director of ChemGenex. P.Z. and J.B. are members of the Scientific Advisory Board of ChemGenex. J.B. also serves as Senior Director of Human Genomics, and K.R.W. serves as Senior Director of Research and Development.

Supplementary information

Supplementary Table 1

Selenoprotein S genetic variation identified in the sample. (PDF 26 kb)

Supplementary Table 2

Distribution of relative pairs in the population sample of 522 individuals from 92 families. (PDF 15 kb)

Supplementary Table 3

siRNA primer sequences. (PDF 13 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Curran, J., Jowett, J., Elliott, K. et al. Genetic variation in selenoprotein S influences inflammatory response. Nat Genet 37, 1234–1241 (2005).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing